• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 1996.12a
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• pp.64-64
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• 1996

Transgenic animal and cell line models which are recently developed in toxicology field combined with molecular biological technique, are powerful tools for studying of mutation in vivo and in vitro, respectively. The Big Blue mutagenesis assay system is one of the most widely used transgenic systems. Especially, for the study of direct acting mutagens, Big Blue cell line is very useful and powerful to evaluate mutagenicity because the mutation frequency and mutationspectrlun showed no distinct differences between cell line and animal. The Big Blue cell lines carry stably integrated copies of lambda shuttle vector containing lac I gene as a mutational target. These lambda shuttle vectors are useful for various mutagenesis related studies in eukaryotic system due to their ability to be exposed mutagen and then transfer a suitable target DNA sequence to it convenient organism for analysis. We tried to assess the mutagenic effect of 4-NQO with Big Blue cell line. After the treatment of 4-NQO, genomic DNA was isolated and lambda shuttle vector was packaged by in Vitro packaging and then these were plated on bacterial host in the presence of X-gal to screen mutation in the lac I. We determined MF as a ratio of blue plaques versus colorless plaques and now undergoing the mutation spectrum of 4-NQO in lac J gene sequence.

• Mycobiology
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• v.49 no.6
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• pp.582-588
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• 2021

The interaction of mating pheromone and pheromone receptor from the B mating-type locus is the first step in the activation of the mushroom mating signal transduction pathway. The B mating-type locus of Lentinula edodes is composed of Bα and Bβ subloci, each of which contains genes for mating pheromone and pheromone receptor. Allelic variations in both subloci generate multiple B mating-types through which L. edodes maintains genetic diversity. In addition to the B mating-type locus, our genomic sequence analysis revealed the presence of a novel chromosomal locus 43.3 kb away from the B mating-type locus, containing genes for a pair of mating pheromones (PHBN1 and PHBN2) and a pheromone receptor (RCBN). The new locus (Bα-N) was homologous to the Bα sublocus, but unlike the multiallelic Bα sublocus, it was highly conserved across the wild and cultivated strains. The interactions of RcbN with various mating pheromones from the B and Bα-N mating-type loci were investigated using yeast model that replaced endogenous yeast mating pheromone receptor STE2 with RCBN. The yeast mating signal transduction pathway was only activated in the presence of PHBN1 or PHBN2 in the RcbN producing yeast, indicating that RcbN interacts with self-pheromones (PHBN1 and PHBN2), not with pheromones from the B mating-type locus. The biological function of the Bα-N locus was suggested to control the expression of A mating-type genes, as evidenced by the increased expression of two A-genes HD1 and HD2 upon the treatment of synthetic PHBN1 and PHBN2 peptides to the monokaryotic strain of L. edodes.

• Therapeutic Science for Rehabilitation
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• v.9 no.3
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• pp.63-75
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• 2020

Objective : The purpose of this study was to examine the changes in work performance and motor function of stroke patients in the Lee Silverman Voice Treatment-BIG (LSVT-BIG) program and to confirm its clinical applicability. Methods : Two stroke patients underwent the LSVT-BIG program for a total of 16 sessions (60 minutes per session and, four days a week for four weeks). To assess any changes between before and after the intervention, the Canadian Occupational Performance Measurement (COPM), Berg Balance Scale (BBS), Timed Up and Go (TUG), Functional Reaching Test (FRT), Manual Function Test (MFT) were used. Differences in scores between before and after the intervention were analyzed. Results : The performance and satisfaction of occupational performance increased after the intervention in both subjects. The performance time of the TUG decreased to 0.91, 8.42 seconds for each subject, increasing the walking speed. In FRT distance change, the subject increased in both the affected side and unaffected side. The BBS score increased by 3 points in one subject and by 6 points in the other, indicating improved balance. In addition, in the MFT score, subject A showed an improvement of 1 point on the unaffected side, and subject B showed an improvement of 1 point on the unaffected side and 3 points on the affected side. Conclusion : We confirmed the applicability of the LSVT-BIG program as a new intervention technique for stroke patients. Future, complementary research on the effects of the LSVT-BIG program on stroke patients will be needed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.54-63
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• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• The Journal of Bigdata
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• v.4 no.1
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• pp.39-51
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• 2019

With the advent of the fourth industrial revolution characterized by hyperconnectivity and superintelligence and the emerging cyber physical systems, enormous volumes of data are being generated in the cyberspace every day ranging from the records about human life and activities to the communication records of computers, information and communication devices, and the Internet of things. Big data represented by 3Vs (volume, velocity, and variety) are actively used in the defence field as well. This paper proposes a big data governance model to support effective military operations in the cyberspace. Cyberspace operation missions and big data types that can be collected in the cyberspace are classified and integrated with big data governance issues to build a big data governance framework model. Then the effectiveness of the constructed model is verified through examples. The result of this study will be able to assist big data utilization planning in the defence sector.

• Knowledge Management Research
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• v.21 no.4
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• pp.243-263
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• 2020

The purpose of this study is to propose the performance measurement model for open big data platform. In order to develop the performance measurement model, we have integrated big data reference architecture(NIST 2018) with performance prism model(Neely et al. 2001) in the platform perspective of open big data. Our proposed model consists of five key building blocks for measuring performance of open data platform as follows: stakeholder contribution, big data governance capabilities, big data service capabilities, big data IT capabilities, and stakeholder satisfaction. In addition, our proposed model have twenty four evaluation indices and seventy five measurement items. We believe that our model could offer both research and practical implications for relevant research.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.179-185
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• 2018

Big Data is strictly positioning one of method to deal with problems faced with mankind, not an icon of revolution in future anymore. Application of Big Data and protection of personal information have contradictoriness. When we weight more to usage of Big Data, someone's privacy is necessarily invaded. otherwise, we care more about keeping safe of individual information, only low-level of research using Big Data can be used to accomplish public purpose. In this study, we propose a method to anonymize Big Data collected in order to investigate the problems of personal information infringement and utilize Big Data and protect personal. This will solve the problem of personal information infringement as well as utilizing Big Data.

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.1
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• pp.148-158
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• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

• Genomics & Informatics
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• v.17 no.4
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• pp.44.1-44.3
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• 2019

Artificial intelligence (AI), big data, and ubiquitous robotic companions -the three most notable technologies of the 4th Industrial Revolution-are receiving renewed attention each day. Technologies that can be experienced in daily life, such as autonomous navigation, real-time translators, and voice recognition services, are already being commercialized in the field of information technology. In the biosciences field in Korea, such technologies have become known to the local public with the introduction of the AI doctor Watson in large number of hospitals. Additionally, AlphaFold, a technology resembling the AI AlphaGo for the game Go, has surpassed the limit on protein folding predictions-the most challenging problems in the field of protein biology. This report discusses the significance of AI technology and big data on the bioscience field. The introduction of automated robots in this field is not just only for the purpose of convenience but a prerequisite for the real sense of AI and the consequent accumulation of basic scientific knowledge.

• Smart Media Journal
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• v.11 no.11
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• pp.49-62
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• 2022

Recently, with the development of Smart City Solutions such as Big data, AI, IoT, Autonomous driving, and Digital twins around the world, the proliferation of various smart devices and social media, and the record of the deeds that people have left everywhere, the construction of Smart Cities using the "Big Data" environment in which so much information and data is produced that it is impossible to gauge the scale is actively underway. The Purpose of this study is to construct an objective and systematic analysis Model based on Big Data to improve the transportation convenience of citizens and formulate efficient policies in Urban Information and Public Transportation accessibility in sustainable Smart Cities following the 4th Industrial Revolution. It is also to derive the methodology of developing a Big Data-Based public transport accessibility and policy management Platform using a sustainable Urban Public DB and a Private DB. To this end, Detailed Living Areas made a division and the accessibility of basic living amenities of Gwangju Metropolitan City, and the Public Transportation system based on Big Data were analyzed. As a result, it was Proposed to construct a Big Data-based Urban Information and Public Transportation accessibility Platform, such as 1) Using Big Data for public transportation network evaluation, 2) Supporting Transportation means/service decision-making based on Big Data, 3) Providing urban traffic network monitoring services, and 4) Analyzing parking demand sources and providing improvement measures.